AI Engineer

Join the Revolution in Vietnamese Fintech!

We're a dynamic fintech startup on a mission to revolutionize how Gen Z and Millennials in Vietnam experience credit, payments and BNPL. Forget clunky processes and outdated apps – we're building a sleek, mobile-first digital credit card and PayLater experience from the ground up. Partnering with a leading bank, we combine stability with cutting-edge tech (think cool SaaS platforms + our own awesome frontend!) to deliver a product that truly understands the digital generation.

Founded by former McKinsey partners and backed by a global VC, we're on the lookout for the next generation of visionaries are not afraid of challenging the status quo. This is your chance to get in on the ground floor, shape a game-changing product, work with the latest tech (including AI!), and make a real impact in one of Southeast Asia's fastest-growing markets (and beyond). If you're ambitious, thrive in a fast-paced startup environment, and want to build something amazing, keep reading!

Role Overview:

• Be our AI pioneer! Identify opportunities and build intelligent solutions across our platform to enhance efficiency, personalization, and risk management.

• Design, develop, and deploy machine learning models for various applications, such as credit risk scoring, fraud detection, transaction categorization, customer segmentation, or personalized offers.

• Collaborate with Data Scientists, Risk Analysts, and Product Managers to understand business problems and translate them into AI/ML solutions.

• Build and manage data pipelines required for training and evaluating ML models.

• Research and experiment with new AI techniques and tools relevant to fintech and credit cards.

• Work on deploying models into production environments, monitoring their performance, and iterating as needed. Champion the use of appropriate AI tools across different functions (e.g., suggesting NLP tools for customer service, computer vision for KYC).

Must-Have Skills & Experience:

• Strong programming skills, particularly in Python, and experience with relevant ML libraries/frameworks (scikit-learn, TensorFlow, PyTorch, Keras).

• Proven 2 years’ experience in developing and deploying machine learning models in a real-world setting.

• Solid understanding of machine learning algorithms (supervised, unsupervised, deep learning), feature engineering, and model evaluation techniques.

• Experience with data manipulation and analysis tools (SQL, Pandas, NumPy).

• Familiarity with cloud platforms (AWS, GCP, Azure) and their AI/ML services (e.g., SageMaker, Vertex AI).

• Strong analytical and problem-solving skills. Broad understanding of available AI tools and their potential applications in business.

Good-to-Have Skills & Experience:

• Master's in Computer Science, AI, Statistics, or a related quantitative field.

• Experience applying AI/ML specifically within fintech, credit risk, or fraud detection.

• Experience with MLOps practices and tools (e.g., MLflow, Kubeflow).

• Experience with big data technologies (Spark, Hadoop).

• Knowledge of natural language processing (NLP) or computer vision techniques.